Merge pull request #1541 from easydiffusion/beta

Beta

CHANGES.md

@@ -17,7 +17,9 @@
 - **Major rewrite of the code** - We've switched to using diffusers under-the-hood, which allows us to release new features faster, and focus on making the UI and installer even easier to use.
 
 ### Detailed changelog
-* 3.0.2 - 30 Aug 2023 - Allow blocking NSFW images using a server-side config. This prevents the browser from generating NSFW images or changing the config. Open `config.yaml` in a text editor (e.g. Notepad), and add `block_nsfw: true` at the end, and save the file.
+* 3.0.3 - 30 Aug 2023 - Allow loading NovelAI-based custom models.
+* 3.0.3 - 30 Aug 2023 - Fix broken VAE tiling. This allows you to create larger images with lesser VRAM usage.
+* 3.0.3 - 30 Aug 2023 - Allow blocking NSFW images using a server-side config. This prevents the browser from generating NSFW images or changing the config. Open `config.yaml` in a text editor (e.g. Notepad), and add `block_nsfw: true` at the end, and save the file.
 * 3.0.2 - 29 Aug 2023 - Fixed incorrect matching of embeddings from prompts.
 * 3.0.2 - 24 Aug 2023 - Fix broken seamless tiling.
 * 3.0.2 - 23 Aug 2023 - Fix styling on mobile devices.

scripts/check_modules.py

@@ -18,7 +18,7 @@ os_name = platform.system()
 modules_to_check = {
     "torch": ("1.11.0", "1.13.1", "2.0.0", "2.0.1"),
     "torchvision": ("0.12.0", "0.14.1", "0.15.1", "0.15.2"),
-    "sdkit": "2.0.5",
+    "sdkit": "2.0.9",
     "stable-diffusion-sdkit": "2.1.4",
     "rich": "12.6.0",
     "uvicorn": "0.19.0",

ui/easydiffusion/types.py

@@ -26,7 +26,7 @@ class GenerateImageRequest(BaseModel):
     sampler_name: str = None  # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
     hypernetwork_strength: float = 0
     lora_alpha: Union[float, List[float]] = 0
-    tiling: str = "none"  # "none", "x", "y", "xy"
+    tiling: str = None  # None, "x", "y", "xy"
 
 
 class FilterImageRequest(BaseModel):

ui/index.html

@@ -35,7 +35,7 @@
             <h1>
                 <img id="logo_img" src="/media/images/icon-512x512.png" >
                 Easy Diffusion
-                <small><span id="version">v3.0.2</span> <span id="updateBranchLabel"></span></small>
+                <small><span id="version">v3.0.3</span> <span id="updateBranchLabel"></span></small>
             </h1>
         </div>
         <div id="server-status">

ui/media/js/dnd.js

@@ -268,7 +268,11 @@ const TASK_MAPPING = {
     tiling: {
         name: "Tiling",
         setUI: (val) => {
-            tilingField.value = val
+            if (val === null || val === "None") {
+                tilingField.value = "none"
+            } else {
+                tilingField.value = val
+            }
         },
         readUI: () => tilingField.value,
         parse: (val) => val,
@@ -583,6 +587,7 @@ const TASK_TEXT_MAPPING = {
     lora_alpha: "LoRA Strength",
     use_controlnet_model: "ControlNet model",
     control_filter_to_apply: "ControlNet Filter",
+    tiling: "Seamless Tiling",
 }
 function parseTaskFromText(str) {
     const taskReqBody = {}

ui/media/js/main.js

@@ -22,7 +22,8 @@ const taskConfigSetup = {
         },
         tiling: {
             label: "Tiling",
-            visible: ({ reqBody }) => reqBody?.tiling != "none",
+            visible: ({ reqBody }) =>
+                reqBody?.tiling != "none" && reqBody?.tiling !== null && reqBody?.tiling !== undefined,
             value: ({ reqBody }) => reqBody?.tiling,
         },
         use_vae_model: {
@@ -680,7 +681,7 @@ function getAllModelNames(type) {
 
 // gets a flattened list of all models of a certain type. e.g. "path/subpath/modelname"
 // use the filter to search for all models having a certain name.
-function getAllModelPathes(type,filter="") {
+function getAllModelPathes(type, filter = "") {
     function f(tree, prefix) {
         if (tree == undefined) {
             return []
@@ -690,7 +691,7 @@ function getAllModelPathes(type,filter="") {
             if (typeof e == "object") {
                 result = result.concat(f(e[1], prefix + e[0] + "/"))
             } else {
-                if (filter=="" || e==filter) {
+                if (filter == "" || e == filter) {
                     result.push(prefix + e)
                 }
             }
@@ -700,7 +701,6 @@ function getAllModelPathes(type,filter="") {
     return f(modelsOptions[type], "")
 }
 
-
 function onUseAsThumbnailClick(req, img) {
     let scale = 1
     let targetWidth = img.naturalWidth
@@ -1237,7 +1237,6 @@ function getCurrentUserRequest() {
             //render_device: undefined, // Set device affinity. Prefer this device, but wont activate.
             use_stable_diffusion_model: stableDiffusionModelField.value,
             clip_skip: clipSkipField.checked,
-            tiling: tilingField.value,
             use_vae_model: vaeModelField.value,
             stream_progress_updates: true,
             stream_image_progress: numOutputsTotal > 50 ? false : streamImageProgressField.checked,
@@ -1302,6 +1301,10 @@ function getCurrentUserRequest() {
             newTask.reqBody.use_lora_model = modelNames
             newTask.reqBody.lora_alpha = modelStrengths
         }
+
+        if (tilingField.value !== "none") {
+            newTask.reqBody.tiling = tilingField.value
+        }
     }
     if (testDiffusers.checked && document.getElementById("toggle-tensorrt-install").innerHTML == "Uninstall") {
         // TRT is installed